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| import gradio as gr | |
| import yolov7 | |
| from yolov7.models.common import autoShape | |
| from yolov7.models.experimental import attempt_load | |
| from yolov7.utils.google_utils import attempt_download_from_hub, attempt_download | |
| from yolov7.utils.torch_utils import TracedModel | |
| YOLO_MODEL_FILE_NAME="kadirnar/yolov7-v0.1" | |
| # YOLO_MODEL_FILE_NAME="kadirnar/yolov7-tiny-v0.1" | |
| def yolov7_inference( | |
| image: gr.inputs.Image = None, | |
| image_size: gr.inputs.Slider = 640, | |
| conf_threshold: gr.inputs.Slider = 0.25, | |
| iou_threshold: gr.inputs.Slider = 0.45, | |
| ): | |
| model = yolov7.load(YOLO_MODEL_FILE_NAME, device="cpu", hf_model=True, trace=False) | |
| model.conf = conf_threshold | |
| model.iou = iou_threshold | |
| results = model([image], size=image_size) | |
| return results.render()[0] | |
| inputs = [ | |
| gr.inputs.Image(type="pil", label="Input Image"), | |
| gr.inputs.Slider(minimum=320, maximum=1280, default=640, step=32, label="Image Size"), | |
| gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.25, step=0.05, label="Confidence Threshold"), | |
| gr.inputs.Slider(minimum=0.0, maximum=1.0, default=0.45, step=0.05, label="IOU Threshold"), | |
| ] | |
| outputs = gr.outputs.Image(type="filepath", label="Output Image") | |
| title = "Yolov7: evaluation yolov7.pt" | |
| examples = [['car.jpeg', 640, 0.5, 0.75], | |
| ['horse.jpeg', 640, 0.5, 0.75]] | |
| demo_app = gr.Interface( | |
| fn=yolov7_inference, | |
| inputs=inputs, | |
| outputs=outputs, | |
| title=title, | |
| examples=examples, | |
| cache_examples=True, | |
| ) | |
| demo_app.launch(debug=True, enable_queue=True) |